results.write(
eli5.format_as_text(
eli5.explain_weights(perm, feature_names=data.columns.tolist())))
##########################################################
#### CREATE SHADOW MODEL IN FORM OF RULE FIT ALGORITHM ###
##########################################################
rf = RuleFit()
rf.fit(X_train, [int(i) for i in Y_train],
feature_names=[
'Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness',
'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age'
])
rules = rf.get_rules()
rules = rules[rules.coef != 0].sort_values("support", ascending=False)
print('\n\nRule Fit aglorithm rules\n' + str(rules))
results.write('\n\nRule Fit aglorithm rules\n' + str(rules))
##############################################################
#### CREATE SHADOW MODEL IN FORM OF Formel Concept Lattice ###
##############################################################
from concepts import Context
## Reading Data
dataset = pd.read_csv('data/diabetes/diabetes_synthesized_data.csv')
dataset.columns = [
'Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin',
'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome'
